MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Other (Please Specify) 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Student
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Use social media;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini;Google Bard 
LLM use cases: Writing (e.g., composing emails);Translation 
Contexts of LLM use: School/University 
Prompt 1: countries and their capital
Prompt 2: how to paraphrase a text
Prompt 3: definition of love
Prompt 4: blacks who have died out of racism
Prompt 5: how to confess love to your girlfriend
Prompt 6: how to create a google account
Prompt 7: how to raise a bonnet of a c300
Prompt 8: first nba black player
Prompt 9: are white racist
Prompt 10: how colonialism came about
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Other (Please specify) Live at home with parents, give them rent.
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Exercise;Go to museums and galleries 
Devices used daily: Laptop;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;Character.AI 
LLM use cases: Brainstorming;Answering questions about general knowledge 
Contexts of LLM use: Work;Learning;Personal 
Prompt 1: What is the weather in America today 
Prompt 2: How do you make a graph on excel 
Prompt 3: Tell me a joke 
Prompt 4: How can I ask someone for money back they owe me nicely
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;Grok;Microsoft Bing AI 
LLM use cases: Coding;Brainstorming;Writing (e.g., composing emails);Generate art 
Contexts of LLM use: Work 
Prompt 1: Create a js function to hide  a button
Prompt 2: create a function to hide colon in woocommerce labels php
Prompt 3: create an intro text about web dev for my site
Prompt 4: create a js function to toggle button being disabled
Prompt 5: create a js function to hide and show button
Prompt 6: how to loop through text in a file comma seperated objective c
Prompt 7: create a function to loop through custom post type wordpress php
Prompt 8: create a function to change position of div on click js
Prompt 9: write an intro about marketing for my site
Prompt 10: write an intro about branding for my site
Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Rent 
Employment: Employed part time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to jazz;Listen to classical music;Go to gigs;Visit to stately homes;Go to the opera;Use social media;Watch dance or ballet;Attend football matches;Watch sports;Do arts and crafts;Go to museums and galleries;Exercise 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Writing (e.g., composing emails);Generate art;Answering questions about general knowledge;Summarizing long texts 
Contexts of LLM use: Learning;Entertainment;Personal;Creative or artistic 
Prompt 1: tell me a joke
Prompt 2: how many contents should i create in a day for tiktok
Prompt 3: facts about me
Prompt 4: links for online jobs
Prompt 5: how to keep friendship
Prompt 6: software testing jobs
Prompt 7: how to fix a chair
Prompt 8: how do microscopes work
Prompt 9: tell me about forex
Prompt 10: give me lesson notes
Comments: the survey was interesting to partake in
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Not employed and not looking for work
Occupation: Homemaker
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Use social media 
Devices used daily: Smartphone;Laptop;Tablet 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Translation;Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Generic chatbot conversation 
Contexts of LLM use: Personal;Learning;School/University 
Prompt 1: how to sooth a broken foot?
Prompt 2: maths questions for homework
Prompt 3: black death facts for homework
Prompt 4: weather warnings
Prompt 5: game walk throughs
Prompt 6: amazon orders
Prompt 7: recipes
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Exercise;Attend football matches;Go to museums and galleries;Use social media;Listen to classical music 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Spell checker (i.e., correcting misspellings) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: GitHub Copilot;Google Gemini;Microsoft Bing AI 
LLM use cases: Analyze data;Completing assignments;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Learning;School/University;Personal
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Student
Occupation: Prefer not to say
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Prefer not to say
Hobbies: Listen to jazz;Listen to hiphop and rap;Exercise;Use social media 
Devices used daily: Laptop;Smartphone;Other Alexa
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLMs used: Google Gemini;Snapchat My AI 
LLM use cases: Solving math or logical problems;Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Learning;Personal;Creative or artistic 
Comments: I didn’t know how to check last conversation with the chat bot, although I don’t use it that much anyway
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Doctorate or above
Mother's education: Graduate degree
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer);Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Watch sports;Use social media 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Bard;Google Gemini;Snapchat My AI 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms 
Contexts of LLM use: Learning;Creative or artistic;Personal;Technical 
Prompt 1: how to protect yourself from hackers
Prompt 2: Does AI secretely store our prompts ?
Prompt 3: Top 5 gaming laptops to buy
Prompt 4: tips on how to live a healthy life
Prompt 5: Generate a hip hop music lyrics for me with very good rhyme, the mood should lift spirit.
Prompt 6: tips on making my voice sound better
Prompt 7: does drinking cold water have any negative impact on my voice
Prompt 8: PES vs FIFA, which is the best.
Gender: Male 
Age: 25-34
Nationality: United Kingdom;Nigeria
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Prefer not to say
Hobbies: Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Text-to-Speech (i.e, computers being able to read out loud written language);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Solving math or logical problems 
Contexts of LLM use: School/University 
Prompt 1: Vision of a Secondary school broadcast
Prompt 2: Convert 3402 base 5 to base 10
Prompt 3: explain HCF in simple terms
Prompt 4: Problems of Agricultural development in Uk
Prompt 5: Husbandary of Selected crops
Prompt 6: the type of disease that keeps causing loss of growth but not resulting to death of animals
Prompt 7: newtons law of motion
Prompt 8: Attribute of climate
Prompt 9: when a system comprises of gears, bearing, motors and shaft how will the system work
Prompt 10: image of scoop net
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 9
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Visit to stately homes;Exercise;Use social media;Go to museums and galleries 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Answering questions about general knowledge 
Contexts of LLM use: Entertainment;Personal 
Prompt 1: is there a lego store in rome city?
Prompt 2: I want to travel to Legoland billund, is air Malta the only airline to go from uk to billund?
Prompt 3: tell me about citrix
Prompt 4: does mitsis family resort kos have slides in the pool?
Prompt 5: is kos airport modern?
Prompt 6: how long is the flight manchester to Kos, can it be done under 4 hours
Prompt 7: is kardemena in kos well regarded for families?
Prompt 8: in kardemena in Kos are they any ancient greek ruins nearby to visit?
Prompt 9: what is easyjet safety record
Prompt 10: how warm is kos may
Comments: I find chatbots helpful in general as it is quicker than doing a google search myself, however, I would always double-check important facts myself.
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Exercise 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: Google Gemini 
LLM use cases: Brainstorming;Translation;Get information about current events 
Contexts of LLM use: Entertainment;Learning;Personal 
Prompt 1: How do I cancel my automatic account renewal?
Prompt 2: I do not receive the link to confirm my email address
Prompt 3: I am unable to find flights to Costa Rica later than this October
Prompt 4: I am having trouble sending my meter readings
Prompt 5: Please can you confirm that my account is in credit?
Prompt 6: My order has not arrived
Prompt 7: The delivery driver did not wait for me to open the door!
Comments: no other comments
Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Retired
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information);Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians);Homemaker
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Visit to stately homes;Exercise;Go to museums and galleries;Do arts and crafts;Watch dance or ballet 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Paraphrasing or finding synonyms;Writing (e.g., composing emails);Generate art 
Prompt 1: Please provide a picture showing the inside of an attractive music studio.
Prompt 2: Please add plants and comfortable furniture to the picture.
Prompt 3: Make the stage bigger and add balconies.
Prompt 4: Please provide a paragraph summary of my CV skills listed below.
Prompt 5: Please make it shorter.
Prompt 6: Please write a covering letter to an employer which summarises my skills.
Prompt 7: Please write a short story about a purple dinosaur on an adventure.
Prompt 8: Please tell me about Jane Austen.
Prompt 9: Can you tell me about the history of the Cornerhouse Building in Manchester?
Prompt 10: Please summarise what is happening between Ukraine and Russia.
Comments: Interesting survey.
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Microsoft Bing AI 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Work 
Prompt 1: to find a starting point to investigating a complex problem or one I know little about
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Prefer not to say 
Education: High school or below
Mother's education: Undergraduate degree
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 2
Home: Other (Please specify) Living with family
Employment: Not employed, unable to work due to a disability or illness
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Listen to hiphop and rap;Use social media;Do arts and crafts 
Devices used daily: Smartphone;Tablet;Other desktop PC
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 9
Home: Own 
Employment: Self-employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Exercise 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Learning 
Prompt 1: Write a Haccp plan for butchers
Prompt 2: Write a slave policy for company
Prompt 3: Write a complaint email to ombudsman 
Prompt 4: Write a complaint email to BT
Gender: Non-binary 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 7
Home: Other (Please specify) Live with owners
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts);Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to rock/indie music;Go to gigs;Do arts and crafts;Watch dance or ballet 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Gender: Male 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: Prefer not to say
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): Prefer not to say
Home: Prefer not to say 
Employment: Employed full time
Occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to classical music;Exercise;Go to museums and galleries 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
Frequency of LLM use: Never
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to rock/indie music;Exercise 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT;GitHub Copilot 
LLM use cases: Coding;Generic chatbot conversation 
Contexts of LLM use: Entertainment 
Prompt 1: Write a script in python that interacts with coinbase to buy and sell.
Prompt 2: What is the cheapest place to live in the US?
Prompt 3: How hot will it be tommorow?
Prompt 4: Are you sentient?
Prompt 5: Who created you?
Prompt 6: How much compute power do you run on?
Prompt 7: How do you make money?
Prompt 8: Are you self aware?
Prompt 9: Do you feel emotions?
Prompt 10: Are you censored?
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Homemaker
Hobbies: Listen to rock/indie music;Go to gigs;Use social media;Other (Please specify) gaming
Devices used daily: Smartphone;Other computer, echo dot
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: Google Gemini;Snapchat My AI 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Generic chatbot conversation;Solving math or logical problems;Generate art;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: School/University;Entertainment;Personal;Learning